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1. Fast simulation of nanoimprint lithography: modelling capillary pressures during resist deformation20 October 2011 Hayden Taylor and Eehern WongSimprint Nanotechnologies LtdBristol, United KingdomNamil Koo, Jung Wuk Kim and Christian MoormannAMICA, AMO GmbH Aachen, Germany hkt@simprintnanotech.com +44 117 2302566 • TexPoint fonts used in EMF. • Read the TexPoint manual before you delete this box.: A

2. Simulation can help select process parameters and refine designs in NIL N Resist surface’s impulse response Example questions: Does changing stamp material affect residual layer uniformity? 1,2 Can ‘dummy fill’ accelerate stamp cavity filling? 3 • Simulations need to be highly scalable • At least 103 times faster than FEM • Can trade off spatial resolution and speed ~O(N2logN) 104 Resist Time (s) 103 Substrate Elastomer Silicon 102 165 99 Stamp’s load response (bending, indentation) 101 (nm) Stamp 101 102 103 104 Simulation size, N 10 92 Resist Pattern abstraction 1 Density 0.5 0 1 Taylor NNT 2009; 2 Taylor SPIE 7641 2010; 3 Boning et al.NNT 2010

3. Chip-scale imprint simulation has until now addressed only thermal NIL Externally applied pressure UV 5 Thermal 4 Resist viscosity during imprinting Stamp 10-2 1 102 104 106 Pa.s Externally applied pressure Capillary forces UV Thermal Resist Capillary pressures Substrate Pressure Low High 10 103 105 107 109 Pa 4e.g. Garcia-Romero, NNT 2008; 5 e.g. Auner, Organic Electronics 10 p.1466 2009

4. We incorporate capillary pressures into our fast NIL simulation algorithm • Need to know: • Resist viscosity, η • Stamp-resist contact angle, θ • Resist’s surface tension, γ Externally applied pressure Stamp Stamp Capillary forces γ Resist θ Substrate η η η Pressure Low High Hydrophilic θ = 90° Hydrophobic

5. A simple modification to the simulation algorithm captures capillary effects γresist surface tension θresist-stamp contact angle s feature pitch w cavity width r r r • pcapillary(x,y) is pattern-dependent. Examples: Consider pressures acting on stamp in quasi-equilibrium: pg pg pg w s γ θ • pcapillary(x,y) falls to zero where cavities are filled • No significant reduction in solution speed compared to thermal NIL simulation

6. Contribution of capillary pressures diminishes with increasing feature size Silicon stamp Resist viscosity 50 mPa Surface tension 28 mN/m Contact angle 30° w

7. The new model has been tested experimentally 50 μm 100 μm Stamp much wider than pattern PDMS stamp E = 1.5 MPa; Thickness >> 150 μm A B C D E Spun-on UVNIL resist Initial thickness: 85–165 nm; Viscosity: 30 mPa.s Silicon substrate Parallel lines: Protrusion width 85 nm Out-of-page length ~ 2 mm Protrusion height nom. 85 nm Parallel lines: Protrusion width 185 nm Out-of-page length ~ 2 mm Protrusion height nom. 85 nm B A D

8. Simulation captures experimentally observed RLT variations Viscosity: 30 mPa.s Stamp

9. Fast capillary-driven filling is followed by residual layer homogenisation Boning, Taylor et al.NNT 2010

10. For droplet-based resist dispensing, a different approach is needed • Phenomena of interest: • Speed of resist spreading 1 • Likelihood of gas bubble entrapment 1-4 • Gas elimination after entrapment 4 1 pL droplet Diameter > 10 μm Reddy et al., Phys Fluids17 122104 (2005) Reddy and Bonnecaze, Microel. Eng. 82 60 (2005) Moriharaet al., Proc NNT 2008 Liang et al., Nanotechnology18 025303 (2007)

11. Pressure distributions can be found for multiple droplets simultaneously Resist viscosity 50 mPa Surface tension 28 mN/m Contact angle 30° Resist thickness 200 nm With zero external pressure: Stamp velocity = 56 nm/ms

12. Summary and outlook • Capillary pressures are added into our spin-on resist simulation algorithm • Minimal increase in computation time • RLT homogenisation time is crucial for spun-on UVNIL processes • A pressure algorithm is proposed for droplet-dispensed NIL Process Chip design Resist model Simulation Engine Physical prediction

13. Acknowledgements • Matthew Dirckx • Theodor Nielsen, Brian Bilenberg and KristianSmistrup at NIL Technology • Duane Boning, MIT • James Freedman, MIT Technology Licensing Office • Mark Breeze

14. Index • Simulation uses • Viscosity/pressures • Model capillary pressures • Integrate with model • Dependence on feature size • Experimental • Model vsexpt • RLT homogenisation • Droplet demo